**4.2 Characteristics of the respondents by wealth ranks**

316 Biogas

To establish the socio-economic profile of the respondents a wealth ranking approach was used. Wealth ranking was important in this study to determine whether there is any relationship between biogas technology adoption and wealth of the household into wealth ranks using a set of pre-established criteria (Afonja, 1992). Since its introduction in the 1980's, rapid rural appraisal (RRA) wealth ranking has become an increasingly accepted means of assessing relative socio-economic status in the context of applied research projects and development programs (Chambers, 1994). In this study the members of village governments were involved in wealth ranking for their respective villagers. Criteria for wealth ranking was adopted as perceived locally it included aspects of, food security, livestock, dairy cattle and other assets ownership, land and annual incomes (Table 2). Results from wealth ranking (based on communities perception) show that there were no people who were really *well off* in the sample of households but only the so called *slightly well-off*. Out of the 120 respondents 22% were *slightly well-off* while l*ess poor* and *poor* were 55% and 27% respectively (Table 2).

*Slightly Well-Off Less Poor The Poor*

Experience food insecurity for about 2 months a year

Limited assets

Keep some livestock, especially dairy cows/indigenous cows, pigs, goats, chickens

Sell more than 30 days of labour per year. May participate in "food-forwork. Household workforce is mainly comprised of children, women and the elderly who command a low daily wage.

(betwee1-2 hectares) Little land (<1 hectares) or landless

None None

Only rarely may experience seasonal food insecurity

Generally have necessities and relatively few other household assets. such as TV, radio, motorcycles

Own some dairy, indigenous cows, pigs, goats, chicken.

Little land

Occasionally may sell less than 30 days labour/year

income >USD 700 Between USD 400-700 Less than USD 400

respondents 22 74 24 % 17.3% 14.7% 12.5%

**4. Results and discussion** 

Food security Generally food

Work for food No HH member

Assets

Livestock

Land

Business/ employment

Annual cash

Sample

secure all the time

Many own various household assets, (cars, motorcycle, bicycles, TV/radio).

Own dairy, indigenous cows, pigs, goats, chicken.

Relatively large land owners (>2 hectares)

works for food

Have a good business or employed

Table 2. Characteristics of each Wealth rank group

**4.1 Wealth ranking of the respondents** 

The empirical evidence suggest that the probability of a household adopting biogas technology increases with decreasing age of the head of household, increasing household income, increasing number of cattle owned, increasing household size, male head of household and increasing cost of traditional fuels (Walekhwa et al., 2009). Also economics, material shortage, operation, and the people's acceptance are considered to be the main factors preventing the diffusion of biogas technology (Taşdemiroǧlu 1988).

Findings on education show the *slightly well-off* respondents to had relatively good education than other categories although the post secondary education was generally low across the three categories. Post secondary education such as vocational and other training is important as it creates professionals and experts including biogas experts in rural areas. The extremely poor spend very little in education hovering around 2% of household budgets (Banerjee (2007). The reason for low spending in education is that children in poor households typically attend public schools or other schools that do not charge a fee even if the education quality is poor. Poor parents are not reacting to the low quality of these schools, either by sending their children to better and more expensive schools or by putting pressure on the government to do something about quality in government schools. This partly occurs because quite often they are illiterate themselves and therefore may have a hard time recognizing that their children are not learning much (Banerjee, 2007).

Regarding family size respondents from *slightly well off* had small family size (3.3 persons) compared to the *less poor* (4.6 persons) and the *poor* (5.9 persons) (Table 3). This could be explained partly by the low levels of education of the poor. The less educated are more likely to start family life early than educated ones and therefore have high chances of having several children in their reproductive life time. These findings are consistent with Banerjee (2007) observation that family size is large for the extremely poor respondents.


Table 3. Characteristics of the respondents

Dairy Farming and the Stagnated Biogas

Use in Rungwe District, Tanzania: An Investigation of the Constraining Factors 319

*poor* (p<2%) categories. However, there was no significant difference of cost of installation between the *less poor* and the *poor* respondents. A major explanation to this is that a high proportion of the *slightly well off* respondents benefited from the pilot project in 1996 when the biogas facilities were installed at half cost by the Danish volunteers. This was a strategy used to sensitise and raise awareness and demand for the biogas facilities. Unfortunately, many people from the *less poor* and the *poor* categories could not take up this opportunity because of many reasons, one of them being risk averse. They wanted to learn from others how it worked and what the advantages were to be. However, by the time they were convinced by the technology and started adopting it, the price had gone back to the market price levels. Another reason for not adopting it during the promotion period was that they had other more pressing issues than biogas, such as a need for cash to carter farming activities and paying for education and health services. Various studies have shown that poor people are always risk averse and therefore it takes time for them to adopt a new technology. Many of the studies about technology adoption conclude that the pace of adopting a new technology in developing countries has been slow among the poor.1 Feder et al., (1985) have identified factors such as aversion to risk and limited access to information as reasons that could partly explain why adoption is slow. Individual characteristics such as education, access to credit, the capacity to bear risk, availability of other inputs and access to

Comparison 1 Slightly Well-off Less Poor Level of significance

In a multiple response question, respondents were asked to mention the constraining factors towards biogas use adoption. The main factors mentioned were that the installation cost was too high (95.8%) and lack of credit facility (95%). Other reasons were lack of expertise (91.7%) and inadequate water (60%) to run the plants. Only a small proportion of 3.3% out of the 120 respondents said they do not need the facility. This may suggest that if the access to biogas is facilitated either through subsidy or access to credits many households in the district could adopt the technology. A comparison across the categories suggest that

635

675

675

(125) \*\*

(250) NS

(176) \*\*\*

information may play a big role in the adoption of the technology.

Wealth Category *Slightly Well-off Less Poor* 

550 (215)

Comparison 2 *Less Poor The Poor*  670 (192)

Comparison 3 *Slightly Well-off The Poor*  550 (250)

Table 5. A comparison of cost (USD) of installation across wealth ranks

NS =not significant, \*\* Significant at p<5%, \*\*\* Significant at p<2%

**4.6 Factors constraining biogas use** 

1 Giné and Klonner , 2005
